Yongwei Sheng

Efficient meltwater drainage through supraglacial streams and rivers on the southwest Greenland ice sheet

Significance Meltwater runoff from the Greenland ice sheet is a key contributor to global sea level rise and is expected to increase in the future, but it has received little observational study. We used satellite and in situ technologies to assess surface drainage conditions on the southwestern ablation surface after an extreme 2012 melting event. We conclude that the ice sheet surface is efficiently drained under optimal conditions, that digital elevation models alone cannot fully describe supraglacial drainage and its connection to subglacial systems, and that predicting outflow from climate models alone, without recognition of subglacial processes, may overestimate true meltwater release from the ice sheet. Thermally incised meltwater channels that flow each summer across melt-prone surfaces of the Greenland ice sheet have received little direct study. We use high-resolution WorldView-1/2 satellite mapping and in situ measurements to characterize supraglacial water storage, drainage pattern, and discharge across 6,812 km2 of southwest Greenland in July 2012, after a record melt event. Efficient surface drainage was routed through 523 high-order stream/river channel networks, all of which terminated in moulins before reaching the ice edge. Low surface water storage (3.6 ± 0.9 cm), negligible impoundment by supraglacial lakes or topographic depressions, and high discharge to moulins (2.54–2.81 cm⋅d−1) indicate that the surface drainage system conveyed its own storage volume every <2 d to the bed. Moulin discharges mapped inside ∼52% of the source ice watershed for Isortoq, a major proglacial river, totaled ∼41–98% of observed proglacial discharge, highlighting the importance of supraglacial river drainage to true outflow from the ice edge. However, Isortoq discharges tended lower than runoff simulations from the Modèle Atmosphérique Régional (MAR) regional climate model (0.056–0.112 km3⋅d−1 vs. ∼0.103 km3⋅d−1), and when integrated over the melt season, totaled just 37–75% of MAR, suggesting nontrivial subglacial water storage even in this melt-prone region of the ice sheet. We conclude that (i) the interior surface of the ice sheet can be efficiently drained under optimal conditions, (ii) that digital elevation models alone cannot fully describe supraglacial drainage and its connection to subglacial systems, and (iii) that predicting outflow from climate models alone, without recognition of subglacial processes, may overestimate true meltwater export from the ice sheet to the ocean.

Quantitative dynamic flood monitoring with NOAA AVHRR

The analysis of the spatial extent and temporal pattern of flood inundation from remotely sensed imagery is of critical importance to flood mitigation. With a high frequency of global coverage, NOAA/AVHRR has the advantage of detecting flood dynamics during devastating floods. In this paper, we describe a systematic approach to flood monitoring using AVHRR data. Four critical issues for successful flood monitoring with AVHRR were identified: correct identification of water bodies, effective reduction of cloud contamination, accurate area estimation of flood extent, and dynamic monitoring of flood processes. In accordance with the spectral characteristics of water and land in AVHRR channels, a simple but effective water identification method was developed with the ability to reduce cloud influences. The area of flooded regions was calculated with the consideration of areal distortion due to map projection, and mixed pixels at water/land boundaries. Flood dynamics were analysed from flood distributions in b...

Response of inland lake dynamics over the Tibetan Plateau to climate change

The water balance of inland lakes on the Tibetan Plateau (TP) involves complex hydrological processes; their dynamics over recent decades is a good indicator of changes in water cycle under rapid global warming. Based on satellite images and extensive field investigations, we demonstrate that a coherent lake growth on the TP interior (TPI) has occurred since the late 1990s in response to a significant global climate change. Closed lakes on the TPI varied heterogeneously during 1976–1999, but expanded coherently and significantly in both lake area and water depth during 1999–2010. Although the decreased potential evaporation and glacier mass loss may contribute to the lake growth since the late 1990s, the significant water surplus is mainly attributed to increased regional precipitation, which, in turn, may be related to changes in large-scale atmospheric circulation, including the intensified Northern Hemisphere summer monsoon (NHSM) circulation and the poleward shift of the Eastern Asian westerlies jet stream.

An automated scheme for glacial lake dynamics mapping using Landsat imagery and digital elevation models: a case study in the Himalayas

Glacial lakes in alpine regions are sensitive to climate change. Mapping and monitoring these lakes would improve our understanding of regional climate change and glacier-related hazards. However, glacial lake mapping over large areas using remote sensing remains a challenge because of various disturbing factors in glacial and periglacial environments. This article presents an automated mapping algorithm based on hierarchical image segmentation and terrain analysis to delineate glacial lake extents. In this algorithm, each glacial lake is delineated with a local segmentation value, and the topographic features derived from digital elevation models (DEMs) are also used to separate mountain shadows from glacial lakes. About 100 scenes of Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images from circa 1990, circa 2000 and 2009 were used to map the glacial lakes and their changes over the entire Himalayas. The results show that the algorithm can map the glacial lakes effectively and efficiently. Mountain shadows or melting glaciers can be differentiated from glacial lakes automatically, and those lakes with mountain shadows can also be identified. Area changes of more than 1000 glacial lakes show that the glacial lakes in the Himalayas have experienced mixed directions of change, while the overall lake areas are expanding at an accelerated rate in the past two decades, indicating great changes to the glacial lakes in the Himalayas.

Downstream Yangtze River levels impacted by Three Gorges Dam

Changes in the Yangtze River level induced by large-scale human water regulation have profound implications on the inundation dynamics of surrounding lakes/wetlands and the integrity of related ecosystems. Using in situ measurements and hydrological simulation, this study reveals an altered Yangtze level regime downstream from the Three Gorges Dam (TGD) to the Yangtze estuary in the East China Sea as a combined result of (i) TGDs flow regulation and (ii) Yangtze channel erosion due to reduced sediment load. During the average annual cycle of TGDs regular flow control in 2009–2012, downstream Yangtze level variations were estimated to have been reduced by 3.9–13.5% at 15 studied gauging stations, manifested as evident level decrease in fall and increase in winter and spring. The impacts on Yangtze levels generally diminished in a longitudinal direction from the TGD to the estuary, with a total time lag of ~9–12 days. Chronic Yangtze channel erosion since the TGD closure has lowered water levels in relation to flows at most downstream stations, which in turn counteracts the anticipated level increase by nearly or over 50% in winter and spring while reinforcing the anticipated level decrease by over 20% in fall. Continuous downstream channel erosion in the near future may further counteract the benefit of increased Yangtze levels during TGDs water supplement in winter and accelerate the receding of inundation areas/levels of downstream lakes in fall.

Characterization of surface water storage changes in Arctic lakes using simulated SWOT measurements

The planned Surface Water and Ocean Topography (SWOT) satellite mission will measure freshwater storage changes in global lakes. Herein, the anticipated SWOT storage change accuracy is evaluated for the lakes in the Peace-Athabasca Delta, Northern Alaska and Western Siberia. Because of the significant lack of Arctic lake measurements, we simulated realistic daily to seasonal changes in water elevations in the study region using a combination of data from lake gauges, satellite radar altimeter, and satellite imagery. This ‘truth’ dataset is sampled with several candidate SWOT orbits and then corrupted with expected instrument errors to simulate SWOT observed storage changes. The number of revisits increases with increasing or decreasing latitude for a given repeat cycle (e.g. four to eight revisits for a 22-day cycle), allowing us to investigate storage change errors at monthly sampling. SWOT storage change accuracy is primarily controlled by lake size. Lakes larger than 1 km2 have relative errors generally less than 5% whereas one-hectare size lakes are about 20%. We concluded that the storage change accuracy is insensitive to the orbital inclination or repeat periods, but is sensitive to lake shapes.

Automated georeferencing and orthorectification of Amazon basin-wide SAR mosaics using SRTM DEM data

Frequently large synthetic aperture radar (SAR) mosaics are not precisely georeferenced because topographic distortions are not removed during the mosaicking process due to the lack of adequate digital elevation models (DEMs). The Shuttle Radar Topography Mission (SRTM) has recently provided high-resolution DEM data with nearly global coverage and makes it possible to rectify SAR mosaics. Though techniques are available for rectifying individual scenes of SAR imagery using DEM data, these methods encounter difficulties when rectifying SAR mosaics because abrupt geometric discontinuities occur in SAR mosaics at scene boundaries. This paper introduces an automated method to removing topographic distortions from SAR mosaics and producing orthorectified mosaics, without accessing original SAR images. The procedures include SAR image simulation from DEMs, two-staged image matching between SAR mosaics and the simulated image, automated tie-point derivation and screening, piecewise image rectification for localized adjustment, and production of orthorectified mosaics. The method is used to orthorectify both high-water and low-water Global Rain Forest Mapping project SAR mosaics covering the entire Amazon basin. Validation results show that one-pixel (i.e., 92 m) positioning accuracy (root mean square error) was achieved in both cases, compared to 14-16 pixel errors (i.e., 1288-1472 m) of the original mosaics.

Automated Image Registration for Hydrologic Change Detection in the Lake-Rich Arctic

Multitemporal remote sensing provides a unique tool to track lake dynamics at the pan-Arctic scale but requires precise registration of thousands of satellite images. This is a challenging task owing to a dearth of stable features to be used as tie points [(TPs), i.e., control points] in the dynamic landscapes. This letter develops an automated method to precisely register images in the lake-rich Arctic. The core premise of the method is that the centers of lakes are generally stable even if their shorelines are not. The proposed procedures first extract lakes in multitemporal satellite images, derive lake centroids and match them between images, and then use the centroids of stable lakes as TPs for image registration. The results show that this approach can achieve subpixel registration accuracy, outcompeting the conventional manual methods in both efficiency and accuracy. The proposed method is fully automated and represents a feasible way to register images for lake change detection at the pan-Arctic scale.

Automated Image Registration Based on Pseudoinvariant Metrics of Dynamic Land-Surface Features

Accurate assessment of land-cover/land-use change is essential for understanding the impacts of global change and necessitates the use of satellite data. Satellite change detection requires large volumes of multitemporal images to be precisely registered. Image registration is particularly difficult in dynamic (i.e., rapidly time varying) landscapes since the changes themselves interfere with the process of tie-point identification. Despite the existence of sophisticated registration algorithms, it is still problematic to register images acquired over such areas due to a dearth of stable features. Hence, we propose an automated image registration method using tie points derived from pseudoinvariant features (PIFs) and apply the method to register satellite images for hydrologic change detection in the Arctic, where abundant shallow lakes dominate the landscape but change significantly over time. A key to the method is the identification of ldquoshape-stablerdquo lakes as PIFs, which preserve their geometric shape even though the shorelines may migrate significantly. The proposed method automatically identifies PIFs based on scale-invariant shape descriptors and employs their center points for establishing the registration model. Our method thus consists of water-body feature extraction, PIF detection based on feature shape criteria, and image registration using tie points derived from the PIFs. The approach is used to register 1978 and 2000 Landsat images in Alaska, where lakes dominate the landscape and change significantly over time. The performance of the proposed approach is evaluated quantitatively, and a high subpixel registration accuracy of 0.66 pixel at Enhanced Thematic Mapper Plus resolution (i.e., 19 m) is achieved. A comparative evaluation indicates that the proposed approach outcompetes the conventional manual tie-point selection method and automated image registration techniques based on fast Fourier transform.

Photo ecometrics for forest inventory

Abstract In this paper, we report the results obtained from the application of digital photogrammetry and hyperspectral data analysis for forest inventory purposes. Our long term goal is to provide low-cost yet accurate estimates of as many important forest biophysical parameters as can be measured and inferred with airborne digital cameras. Accuracies of traditional multispectral image analysis algorithms of remotely sensed data are low. Traditional photo interpretation is error prone and expensive. We propose new image analysis strategies that make use of the 3D spatial morphological information from stereo images and the multispectral, texture and contextual information inherent in the imagery. Research on the use of 3D crown shape information in automated tree species recognition has not been reported before. The minimum requirements of image spatial resolution for deriving estimates of tree heights and crown size with high accuracies are not known. With digital photogrammetry, it has been proven that...